termplot                package:base                R Documentation

_P_l_o_t _r_e_g_r_e_s_s_i_o_n _t_e_r_m_s

_D_e_s_c_r_i_p_t_i_o_n:

     Plots regression terms against their predictors, optionally with
     standard errors and partial residuals added.

_U_s_a_g_e:

     termplot(model, data=NULL, envir=environment(formula(model)),
              partial.resid=FALSE, rug=FALSE,
              terms=NULL, se=FALSE, xlabs=NULL, ylabs=NULL, main = NULL,
              col.term = 2, lwd.term = 1.5,
              col.se = "orange", lty.se = 2, lwd.se = 1,
              col.res = "gray", cex = 1, pch = par("pch"),
              ask = interactive() && nb.fig < n.tms && .Device !="postscript",
              use.factor.levels=TRUE,
              ...)

_A_r_g_u_m_e_n_t_s:

   model: fitted model object

    data: data frame in which variables in 'model' can be found

   envir: environment in which variables in 'model' can be found

partial.resid: logical; should partial residuals be plotted?

     rug: add rugplots (jittered 1-d histograms) to the axes?

   terms: which terms to plot (default 'NULL' means all terms)

      se: plot pointwise standard errors?

   xlabs: vector of labels for the x axes

   ylabs: vector of labels for the y axes

    main: logical, or vector of main titles;  if 'TRUE', the model's
          call is taken as main title, 'NULL' or 'FALSE' mean no
          titles.

col.term, lwd.term: color and line width for the "term curve", see
          'lines'.

col.se, lty.se, lwd.se: color, line type and line width for the
          "twice-standard-error curve" when 'se = TRUE'.

col.res, cex, pch: color, plotting character expansion and type for
          partial residuals, when 'partial.resid = TRUE', see 'points'.

     ask: logical; if 'TRUE', the user is _ask_ed before each plot, see
          'par(ask=.)'.

use.factor.levels: Should x-axis ticks use factor levels or numbers for
          factor terms?

     ...: other graphical parameters

_D_e_t_a_i_l_s:

     The model object must have a 'predict' method that accepts
     'type=terms', eg 'glm' in the'base' package, 'coxph' and 'survreg'
     in the 'survival' package.

     For the 'partial.resid=TRUE' option it must have a 'residuals'
     method that accepts 'type="partial"', which 'lm' and 'glm' do.

     The 'data' argument should rarely be needed, but in some cases
     'termplot' may be unable to reconstruct the original data frame.

     Nothing sensible happens for interaction terms.

_S_e_e _A_l_s_o:

     For (generalized) linear models, 'plot.lm' and 'predict.glm'.

_E_x_a_m_p_l_e_s:

     had.splines <- "package:splines" %in% search()
     if(!had.splines) rs <- require(splines)
     x <- 1:100
     z <- factor(rep(LETTERS[1:4],25))
     y <- rnorm(100,sin(x/10)+as.numeric(z))
     model <- glm(y ~ ns(x,6) + z)

     par(mfrow=c(2,2)) ## 2 x 2 plots for same model :
     termplot(model, main = paste("termplot( ", deparse(model$call)," ...)"))
     termplot(model, rug=TRUE)
     termplot(model, partial=TRUE, rug= TRUE,
              main="termplot(..., partial = TRUE, rug = TRUE)")
     termplot(model, partial=TRUE, se = TRUE, main = TRUE)
     if(!had.splines && rs) detach("package:splines")

